Jyoteshwar R. Nagol

• PhD
• Professor (Assistant) at University of Maryland, College Park

Solar induced fluorescence (SIF) is an ecological variable of interest to remote sensing retrievals, as it is directly related to vegetation composition and condition. FIREFLY (fluorescence imaging of red and far-red light yield) is a high performance spectrometer for estimating SIF. FIREFLY was flown in conjunction with NASA Goddard’s lidar, hyper...

Forage availability and predation risk interact to affect habitat use of ungulates across many biomes. Within sky‐island habitats of the Mojave Desert, increased availability of diverse forage and cover may provide ungulates with unique opportunities to extend nutrient uptake and/or to mitigate predation risk. We addressed whether habitat use and f...

Tree height growth measurements at monthly and annual time scales are important for calibrating and validating forest growth models, forest management and studies of forest ecology and biophysical processes. Previous studies measured the terminal growth of individual trees or forest stands at annual or decadal time scales. Short-term, within-season...

Vegetation phenology is commonly studied using time series of multi-spectral vegetation indices derived from satellite imagery. Differences in reflectance among land-cover and/or plant functional types are obscured by sub-pixel mixing, and so phenological analyses have typically sought to maximize the compositional purity of input satellite data by...

The Advanced Very High Resolution Radiometer (AVHRR) sensor provides a unique global remote sensing dataset that ranges from the 1980s to the present. Over the years, several efforts have been made on the calibration of the different instruments to establish a consistent land surface reflectance time-series and to augment the AVHRR data record with...

Since 1945, over $4.9 trillion dollars of international aid has been allocated to developing countries. To date, there have been no estimates of the regional impact of this aid on the carbon cycle. We apply a geographically explicit matching method to estimate the relative impact of large-scale World Bank projects implemented between 2000 and 2010...

The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primar...

Literature sources used to calculate date-of-birth (DOB) for migratory mule deer (Odocoileus hemionus) in the southwestern United States. (DOCX)

Natural events such as earthquakes, floods, hurricanes, tsunamis have occurred throughout Earth’s history. These are caused by naturally occurring processes and are considered natural hazards and disasters because they negatively affect humans and destroy livelihoods. On the other hand, technological disasters like oil and chemical spills, pollutio...

Since the 2008 opening of the USGS Landsat archive, research has focused on standardization and compositing of dense time series of Landsat images to increase measurement precision sufficiently for long-term and/or global land cover mapping. Most of these efforts rely on atmospherically corrected estimates of surface reflectance, some of which also...

The Normalized Difference Vegetation Index (NDVI) time-series data derived from Advanced Very High Resolution Radiometer (AVHRR) have been extensively used for studying inter-annual dynamics of global and regional vegetation. However, there can be significant uncertainties in the data due to incomplete atmospheric correction and orbital drift of th...

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data. We evaluated four potential mechanisms for the seasonal green-up p...

Global vegetation models predict rapid poleward migration of tundra and boreal forest vegetation in response to climate warming. Local plot and air-photo studies have documented recent changes in high-latitude vegetation composition and structure, consistent with warming trends. To bridge these two scales of inference, we analyzed a 24-year (198620...

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging S...

Near-surface air temperature governs a range of land surface processes, such as photosynthesis, respiration, and evapotranspiration. However, the spatiotemporal patterns of near-surface air temperature are complex. Meteorological stations provide a detailed account of temporal variations in air temperature, but fail to capture spatial heterogeneity...

Dynamic Global Vegetation Models (DGVMs) generally predict poleward migration of temperate and boreal vegetation biomes in response to climate warming. Some models anticipate rapid migration of these biomes during the 21st century, suggesting that local vegetation shifts should already be observable in the satellite record. We have examined trends...

The seasonality of light and moisture availability governs net ecosystem production in tropical forests. Whether tropical forest productivity is more limited by light or moisture remains an area of active debate. Recent satellite-based studies support the light limitation hypothesis, as Amazon forests respond with higher productivity through leaf t...

Several influential Earth system science studies in the last three decades were based on Normalized Difference Vegetation Index (NDVI) data from Advanced Very High Resolution Radiometer (AVHRR) series of instruments. Although AVHRR NDVI data are known to have significant uncertainties resulting from incomplete atmospheric correction, orbital drift,...

The data from AVHRR (Advanced Very High Resolution Radiometer) series of instruments have frequently been used for vegetation studies. The nearly three decades long AVHRR data record enabled important time-series studies. Many applications use NDVI (Normalized Difference Vegetation Index), or its derivatives, as their operational variable. For long...

The AVHRR (Advanced Very High Resolution Radiometer) series of instruments has frequently been used for vegetation studies. The 25+ year record has enabled important time-series studies. Many applications use NDVI (Normalized Difference Vegetation Index), or derivatives of it, as their operational variable. However, most AVHRR datasets have incompl...

The Normalized Difference Vegetation Index (NDVI) time-series data derived from Advanced Very High Resolution Radiometer (AVHRR) have been extensively used for studying inter-annual dynamics of global and regional vegetation. However there are significant variations in the data as a result of the orbital drift of the satellites through their active...

Data derived from the AVHRR (Advanced Very High Resolution Radiometer) series of instruments has been extensively used for monitoring global and regional vegetation dynamics for last 25+ years. Past studies have shown that the influence of systematic change in satellite overpass time during the course of satellite's life due to orbital drift remain...

The goal of NASA's land long term data record (LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05deg, which is identical to the climate modeling...

Vegetation index data derived from the AVHRR (Advanced Very High Resolution Radiometer) series of instruments has been extensively used for monitoring global and regional vegetation dynamics for last 25+ years. Many of these studies make use of NDVI (Normalized Difference Vegetation Index) or products derived from NDVI as their operational variable...

The relationship between the Normalized Difference Vegetation Index (NDVI) and surface skin temperature (Ts), the Temperature-Vegetation Index (TVX), generally exhibits a negative relationship where vegetation has a high NDVI and low temperature and bare soil has a low NDVI and higher temperature. This relationship has been utilized to study air te...